Evidence map›Paper›PMID 34450967›Full record

ArticleSensors (Basel, Switzerland)2021

Effects of Sensor Types and Angular Velocity Computational Methods in Field Measurements of Occupational Upper Arm and Trunk Postures and Movements.

Xuelong Fan, Carl Mikael Lind, Ida-Märta Rhen, Mikael Forsman

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xuelong FanIMM Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden.ORCID 0000-0003-4145-5717
Carl Mikael LindIMM Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden.ORCID 0000-0001-5979-5504
Ida-Märta RhenIMM Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
Mikael ForsmanIMM Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden.ORCID 0000-0001-5777-4232

Funding

AFA Försäkring 180098AFA Försäkring 180254China Scholarship Council 201600160060
6 · The paper itself

Abstract

Accelerometer-based inclinometers have dominated kinematic measurements in previous field studies, while the use of inertial measurement units that additionally include gyroscopes is rapidly increasing. Recent laboratory studies suggest that these two sensor types and the two commonly used angular velocity computational methods may produce substantially different results. The aim of this study was, therefore, to evaluate the effects of sensor types and angular velocity computational methods on the measures of work postures and movements in a real occupational setting. Half-workday recordings of arm and trunk postures, and movements from 38 warehouse workers were compared using two sensor types: accelerometers versus accelerometers with gyroscopes-and using two angular velocity computational methods, i.e., inclination velocity versus generalized velocity. The results showed an overall small difference (<2° and value independent) for posture percentiles between the two sensor types, but substantial differences in movement percentiles both between the sensor types and between the angular computational methods. For example, the group mean of the 50th percentiles were for accelerometers: 71°/s (generalized velocity) and 33°/s (inclination velocity)-and for accelerometers with gyroscopes: 31°/s (generalized velocity) and 16°/s (inclination velocity). The significant effects of sensor types and angular computational methods on angular velocity measures in field work are important in inter-study comparisons and in comparisons to recommended threshold limit values.

Indexed as

ArmPostureBiomechanical PhenomenaHumansMovementaccelerometerbiomechanicsergonomicsfield measurementinertial measurement unitkinematicsmusculoskeletal disorderssensor fusionthreshold limit valueworkload

Identifiers

PMID34450967
PMCPMC8401405

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.